Digital images have become more popular in the field of image display because they offer clarity and less distortion during processing. Furthermore, a wider range of image processing algorithms can be applied to digital images. Interpolation is a common stage in image processing to improve the appearance of the processed image on the output imaging medium. Interpolation is often performed during rescaling or resizing of digital images.
Rescaling or resizing of digital images includes magnification or reduction of image. For example, large screen displays have a native resolution that reaches or exceeds the well-known high-definition TV (HDTV) standard. In order to display a low-resolution digital image on a large screen display, it is desirable to rescale the image to a full screen resolution.
Traditionally, linear interpolation techniques such as bilinear or bicubic interpolation are used to rescale digital images. The bilinear interpolation method interpolates an input signal using a 2-tap filter. In this method, only the two pixels immediately on either side of the location of the new pixel are used. The bicubic interpolation method interpolates an input signal using a 4-tap filter. In this method, two pixels on either side of the location of the new pixel are used.
2-tap and 4-tap filters all have degradation in the high frequency region. These filters often suffer from image quality issues, such as blurring, aliasing, and staircase edges. 8-tap interpolation, such as that performed by an 8-tap polyphase filter, improves reconstruction in the high frequency region and reduces the staircase and aliasing issues. However, 8-tap interpolation introduces ringing artifacts along the edges, and the conventional 8-tap interpolation is not flexible in sharpness control.